ARTIFICIAL INTELLIGENCE-DRIVEN MICROBIAL BIOTECHNOLOGY: ADVANCES IN METAGENOMICS, ENZYME ENGINEERING, AND SUSTAINABLE BIOPROCESS OPTIMIZATION

Abstract

Artificial Intelligence (AI) has become a transformative strategy in microbial biotechnology, offering potential for enhancing microbial identification, functional prediction, enzyme engineering, and optimizing sustainable bioprocesses. This review focuses on the advancements in microbial biotechnology, particularly in the areas of metagenomics, enzyme discovery, and sustainable industrial applications, as influenced by AI. Advances in computational modelling, machine learning and deep learning have enabled more effective identification of microbial communities, functional genes and metabolic pathways, taking the analysis of complex microbial information further. AI can also be used to analyse microbial diversity and discover biologically valuable compounds using metagenomics, or for computational enzyme engineering to predict enzyme functions, substrate specificity, and catalytic properties. Furthermore, AI-driven bioprocess optimization can facilitate optimization of fermentation processes, AI-driven smart monitoring of bioreactors, resource utilization, and sustainable biomanufacturing. However, certain issues around biological data quality, model interpretability, computational load, experimental validation, and industrial applicability remain and further limit the use of these models. The prospect of using new technologies like generative AI, synthetic biology, automated experimentation, and digital twin systems in the field of microbial engineering and process automation is exciting. The future research should focus on robust computational models, bio information standardization, interdisciplinary collaborative applications and applications validated by the experiments. In conclusion, the intersection of AI and microbial biotechnology presents a vast realm of possibilities for discovery, efficiency, sustainability, and responsible application in the biotechnology industry, while also ensuring the responsible integration of technology and ongoing innovation.